
import os
import unittest

from transformers import LayoutLMTokenizer, LayoutLMTokenizerFast
from transformers.models.layoutlm.tokenization_layoutlm import VOCAB_FILES_NAMES
from transformers.testing_utils import require_tokenizers

from ...test_tokenization_common import TokenizerTesterMixin




@require_tokenizers
class 			UpperCAmelCase_     (					_A    ,			unittest.TestCase	):


  '''simple docstring'''







  a__       			=						LayoutLMTokenizer
  a__       			=						LayoutLMTokenizerFast
  a__       			=						True
  a__       			=						True
  def 				_lowercase				(					self     :					Tuple       )     ->      Optional[int]:







    """simple docstring"""






    super().setUp()

    __magic_name__								=			[
        """[UNK]""",
        """[CLS]""",
        """[SEP]""",
        """want""",
        """##want""",
        """##ed""",
        """wa""",
        """un""",
        """runn""",
        """##ing""",
        """,""",
        """low""",
        """lowest""",
    ]
    __magic_name__								=			os.path.join(self.tmpdirname     ,				VOCAB_FILES_NAMES["""vocab_file"""]       )
    with open(self.vocab_file     ,				"""w"""     ,				encoding="""utf-8"""       ) as vocab_writer:
      vocab_writer.write("""""".join([x + """\n""" for x in vocab_tokens]       )       )
  def 				_lowercase				(					self     :					List[Any]     ,				**UpperCamelCase__     :					Optional[int]       )     ->      Optional[Any]:







    """simple docstring"""






    return LayoutLMTokenizer.from_pretrained(self.tmpdirname     ,				**UpperCamelCase__       )
  def 				_lowercase				(					self     :					List[Any]     ,				UpperCamelCase__     :					Dict       )     ->      List[Any]:







    """simple docstring"""






    __magic_name__								=			"""UNwant\u00E9d,running"""
    __magic_name__								=			"""unwanted, running"""
    return input_text, output_text
  def 				_lowercase				(					self     :					Optional[int]       )     ->      List[Any]:







    """simple docstring"""






    __magic_name__								=			self.tokenizer_class(self.vocab_file       )

    __magic_name__								=			tokenizer.tokenize("""UNwant\u00E9d,running"""       )
    self.assertListEqual(UpperCamelCase__     ,				["""un""", """##want""", """##ed""", """,""", """runn""", """##ing"""]       )
    self.assertListEqual(tokenizer.convert_tokens_to_ids(UpperCamelCase__       )     ,				[7, 4, 5, 10, 8, 9]       )





  def 				_lowercase				(					self     :					Optional[Any]       )     ->      Any:







    """simple docstring"""






    pass



import warnings

from ...utils import logging
from .image_processing_beit import BeitImageProcessor


__lowerCAmelCase     :	int       			=  logging.get_logger(__name__)




class 			UpperCAmelCase_     (					_A	):


  '''simple docstring'''







  def __init__(					self     :					int     ,				*UpperCamelCase__     :					Optional[Any]     ,				**UpperCamelCase__     :					Optional[Any]       )     ->      None:







    """simple docstring"""






    warnings.warn(
        """The class BeitFeatureExtractor is deprecated and will be removed in version 5 of Transformers. Please"""
        """ use BeitImageProcessor instead."""     ,				UpperCamelCase__     ,				)
    super().__init__(*UpperCamelCase__     ,				**UpperCamelCase__       )

